Missing values treatment in agronomy dataset using PCA-Based Multiple Imputation (Bootstrap versus Bayesian)
Missing values are prevalent in agronomy datasets and need consideration to ensure the applicability of statistical methods and avoid bias in treating them. Previous studies indicate that multiple imputation is more effective than single imputation, with Principal Component Analysis (PCA)-based meth...
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| Main Authors: | , |
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| Format: | Article |
| Language: | en |
| Published: |
Penerbit Universiti Kebangsaan Malaysia
2025
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| Online Access: | http://journalarticle.ukm.my/26407/1/Paper_1%20-.pdf http://journalarticle.ukm.my/26407/ https://www.ukm.my/jqma/ |
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